Error handling strategies in a spoken dialogue system
Rolf Carlson, Jens Edlund and Gabriel Skantze
- Error handling research issues
- The long term research goals of the project include these items, which permeate shorter term research issues:
- How do different levels of feedback and detail in system responses affect robustness and efficiency of the dialogue?
- Which factors should govern the dialogue strategy regarding feedback and information detail?
- How can the different system modules calculate confidence measures?
- How can we categorise errors regarding the types of error handling they demand?
- How should the system act when it doesn't understand, or only partially understands, what the user says?
- How does the user's beliefs about the system’s understanding correlate to its actual understanding, depending on error handling strategy?
- The HIGGINS domain
- The primary domain of HIGGINS is city navigation for pedestrians.
- Secondarily, HIGGINS is intended to provide simple information about the immediate surroundings.
- We endeavour to follow these design principles:
- The dialogue system is distributed and module based, which makes switches between different system configurations easier.
- The modules are built to be versatile and it is simple to test different module internal configurations.
- Empirical iterations
- Modules are based on experiences drawn from empirical data, when possible.
- Modules are built to be testable against empirical data.
User:I want to go to the closest subway station.
System:Ok, to the closest subway station. Can you describe where you are now?
User: I have an ATM to my left and a pedestrian crossing in front of me.
System:Can you see some trees to your right and a white building in front of you?
System:Ok, take left after the large building which you have on your left and follow the street until you reach a crossing.
User:Ok, there is a bus station here.
System:That’s right. Take left again after the bus station.
- Current research issues
- A sample of the issues we are currently working on:
- Which robust parsing techniques are suitable for more complex utterances?
- The HIGGINS parser presently achieves robust parsing by using grammars allowing insertions, fragments and non-congruence.
- How does a dialogue manager that is able to vary its feedback level make its choices?
- The HIGGINS parser produces confidence measures which may be combined with ASR confidence to provide a basis for selecting feedback level.
- How can incremental speech recognition be utilised to improve dialogue?
- The HIGGINS parser supports incremental parsing that facilitates fast feedback, which could help the user detect and correct errors.
- What demands on interpretation and error handling are specific for the chosen domain?
- Pedestrian navigation dialogues and human error handling strategies has been collected in a modified Wizard of Oz setting.
- Spatial descriptions in a simulated 3D environment are currently being collected.
- Domain challenges
- The system should be able to:
- Represent complex properties of objects as well as relations between objects.
- Make morphological distinctions between singular/plural, definite/indefinite.
- Engage in a dialogue to find out the user’s destination and then iteratively update a hypothesis of the user’s position based on the user’s descriptions of the surroundings.
- Compute the user’s position using spatial and temporal reasoning.
- Engage in an extended dialogue in case the user’s descriptions are insufficient for determining the position.
- Generate route directions in appropriately sized chunks, providing the optimal path and using grounded concepts in the directions.